Articles written in Sadhana
Volume 46 All articles Published: 3 February 2021 Article ID 0024
Scientific Text Entailment and a Textual-Entailment-based framework for cooking domain question answering
AMARNATH PATHAK RIYANKA MANNA PARTHA PAKRAY DIPANKAR DAS ALEXANDER GELBUKH SIVAJI BANDYOPADHYAY
Detecting entailment relationship between two sentences has profoundly impacted several different application areas of Natural Language Processing (NLP). Though recognizing textual entailment (TE) is amongst the widely studied problems, the research on detecting entailment between pieces of scientific texts is still in its infancy. To this end the paper discusses implementation of systems based on Long Short-Term Memory (LSTM) neural network and Support Vector Machine (SVM) classifiers using SCITAIL entailment dataset, a dataset in which premise and hypothesis are constituted of scientific texts. Also, a TE-based framework for cooking domain question answering is introduced. The proposed framework exploits the entailment relationship between user question and the cooking questions contained inside a Knowledge Base (KB).
Volume 47 All articles Published: 14 November 2022 Article ID 0238
Investigation of negation effect for English–Assamese machine translation
SAHINUR RAHMAN LASKAR ABINASH GOGOI SAMUDRANIL DUTTA PROTTAY KUMAR ADHIKARY PRACHURYA NATH PARTHA PAKRAY SIVAJI BANDYOPADHYAY
Computational linguistics deals with the computational modelling of natural languages, in which machine translation is a popular task. The aim of machine translation is to automatically translate one natural language into another, which minimizes the linguistic barrier of different linguistic backgrounds. The datadrivenapproach of machine translation, namely, neural machine translation achieves state-of-the-art results on different language pairs, however it needs a sufficient amount of parallel training data to attain reasonable translation performance. In this work, we have explored different machine translation models on a low-resource English–Assamese language pair and investigated different sources of errors, particularly due to negation in English-to-Assamese and Assamese-to-English translation. Negation is a universal, essential feature of humanlanguage that has a substantial impact on the semantics of a statement. Moreover, a rule-based approach is proposed in the data preprocessing step which handles modal-verb negation problem that shows significant improvement in translation performance in terms of automatic and manual evaluation scores.
Volume 48, 2023
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